| Publication type: | Article in scientific journal |
| Type of review: | Peer review (publication) |
| Title: | A classification framework for predicting components' remaining useful life based on discrete-event diagnostic data |
| Authors: | Fink, Olga Zio, Enrico Weidmann, Ulrich |
| DOI: | 10.1109/TR.2015.2440531 |
| Published in: | IEEE Transactions on Reliability |
| Volume(Issue): | 64 |
| Issue: | 3 |
| Page(s): | 1049 |
| Pages to: | 1056 |
| Issue Date: | 2015 |
| Publisher / Ed. Institution: | IEEE |
| ISSN: | 0018-9529 1558-1721 |
| Language: | English |
| Subject (DDC): | 006: Special computer methods |
| Abstract: | In this paper, we propose to define the problem of predicting the remaining useful life of a component as a binary classification task. This approach is particularly useful for problems in which the evolution of the system condition is described by a combination of a large number of discrete-event diagnostic data, and for which alternative approaches are either not applicable, or are only applicable with significant limitations or with a large computational burden. The proposed approach is demonstrated with a case study of real discrete-event data for predicting the occurrence of railway operation disruptions. For the classification task, Extreme Learning Machine (ELM) has been chosen because of its good generalization ability, computational efficiency, and low requirements on parameter tuning. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/13902 |
| Fulltext version: | Published version |
| License (according to publishing contract): | Licence according to publishing contract |
| Departement: | School of Engineering |
| Organisational Unit: | Institute of Data Analysis and Process Design (IDP) |
| Appears in collections: | Publikationen School of Engineering |
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Fink, O., Zio, E., & Weidmann, U. (2015). A classification framework for predicting components’ remaining useful life based on discrete-event diagnostic data. IEEE Transactions on Reliability, 64(3), 1049–1056. https://doi.org/10.1109/TR.2015.2440531
Fink, O., Zio, E. and Weidmann, U. (2015) ‘A classification framework for predicting components” remaining useful life based on discrete-event diagnostic data’, IEEE Transactions on Reliability, 64(3), pp. 1049–1056. Available at: https://doi.org/10.1109/TR.2015.2440531.
O. Fink, E. Zio, and U. Weidmann, “A classification framework for predicting components’ remaining useful life based on discrete-event diagnostic data,” IEEE Transactions on Reliability, vol. 64, no. 3, pp. 1049–1056, 2015, doi: 10.1109/TR.2015.2440531.
FINK, Olga, Enrico ZIO und Ulrich WEIDMANN, 2015. A classification framework for predicting components‘ remaining useful life based on discrete-event diagnostic data. IEEE Transactions on Reliability. 2015. Bd. 64, Nr. 3, S. 1049–1056. DOI 10.1109/TR.2015.2440531
Fink, Olga, Enrico Zio, and Ulrich Weidmann. 2015. “A Classification Framework for Predicting Components’ Remaining Useful Life Based on Discrete-Event Diagnostic Data.” IEEE Transactions on Reliability 64 (3): 1049–56. https://doi.org/10.1109/TR.2015.2440531.
Fink, Olga, et al. “A Classification Framework for Predicting Components’ Remaining Useful Life Based on Discrete-Event Diagnostic Data.” IEEE Transactions on Reliability, vol. 64, no. 3, 2015, pp. 1049–56, https://doi.org/10.1109/TR.2015.2440531.
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